IBM has taken computing in a new direction with a new computer to human interface they've dubbed Watson. When Intel's co-founder, Moore , wrote a paper and made predictions nearly half a century past it is doubtful he had a concrete vision of how important technology would become to society.
The doubling of transistor count on circuits every eighteen to twenty months has given way to technologies which have diminished in physical stature while being able to do exponentially more than what the first lunar lander was capable. IBM seems to be carrying on the doubling tradition with an interesting new twist: allowing a computer to learn from it's mistakes, and to account for the inconsistencies in human language in a bid to bridge the communication gap between mankind and machines.
The DeepQA Project is the foundation on which Watson stands. The projects intent is to allow Watson to interpret and react to a wide array of human-centric verbal cues. While not a strong Artificial Intelligence, Watson relies on the algorithms it has been preloaded with and thus is somewhat limited, it can hone the algorithms to produce more accurate results. To account for the variety of questions that could be asked of it Watson runs all of it's algorithms simultaneously and then runs their results back through a final algorithm for accuracy. The project is ambitious in it's goals and has achieved them, as seen in Watson's first public trial, being pitted against the reigning champions of Jeopardy at their own game.
Overview
IBM has taken computing in a new direction with a new computer to human interface they've dubbed Watson. When Intel's co-founder, Moore , wrote a paper and made predictions nearly half a century past it is doubtful he had a concrete vision of how important technology would become to society.The doubling of transistor count on circuits every eighteen to twenty months has given way to technologies which have diminished in physical stature while being able to do exponentially more than what the first lunar lander was capable. IBM seems to be carrying on the doubling tradition with an interesting new twist: allowing a computer to learn from it's mistakes, and to account for the inconsistencies in human language in a bid to bridge the communication gap between mankind and machines.
The DeepQA Project is the foundation on which Watson stands. The projects intent is to allow Watson to interpret and react to a wide array of human-centric verbal cues. While not a strong Artificial Intelligence, Watson relies on the algorithms it has been preloaded with and thus is somewhat limited, it can hone the algorithms to produce more accurate results. To account for the variety of questions that could be asked of it Watson runs all of it's algorithms simultaneously and then runs their results back through a final algorithm for accuracy. The project is ambitious in it's goals and has achieved them, as seen in Watson's first public trial, being pitted against the reigning champions of Jeopardy at their own game.
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